Graduate Product Analyst

As a Graduate Product Analyst, you’ll join our North America Regional Analytics team in September 2027. This full-time role is a chance to make a real impact early and kickstart your career. You’ll be onboarded with the global Graduate cohort in one of our offices and learn the basics of being a Wiser. ## The Role We’re hiring three graduates to work as analysts inside our North America product teams, which build Wise for personal and business customers in the US and Canada. Our analysts don’t sit in a central reporting team: each one works day to day with product managers and engineers and helps them decide what to build next and whether it worked. You’ll join one of four teams: Onboarding, Send, Account or Growth. You won’t be on your own. A senior analyst will mentor you, review your work and help you grow, and you’ll be part of a team of analysts covering the whole North America product. ## What you’ll be doing - Shape Strategy & Prioritization: Help your team understand where customers struggle and what is worth fixing first, by digging into funnels and customer behavior, reading customer feedback and survey responses, and sizing opportunities so the team can prioritize the work with the biggest impact. - Learn Launch Rigor & Experimentation: Help design and analyze A/B tests and pre/post comparisons for new features, and turn the results into a clear call: roll out, iterate or roll back. Keep an eye on your team’s core metrics and flag when something looks wrong. - Build on the Semantic Layer: Learn to build and maintain the data models and dashboards that let your team answer their own questions, using Snowflake, dbt, Git, Airflow, Python and Lightdash, and help improve the AI skills that run our routine reporting. - Share What You Learn: Explain your findings to your team and the wider NorthAm squad, in writing, in charts and in person, so that your work leads to a decision. ## How we work with AI AI skills produce our routine work and deep dives, so our analysts can focus on discovery. You’ll use AI tools every day, and you’ll own the answer, not the tool: checking the data, the logic and the conclusion before anyone acts on it. ## Where you could join - Onboarding: Owns creating a profile, getting verified (Know Your Customer / Know Your Business checks), taking a first action with Wise, and keeping financial crime out at the front door. - Send: Covers what happens when a customer sends money, through three teams: Pay-in (payment methods, including bank transfer (ACH) and card), Payout (how money reaches recipients’ bank accounts in the US and Canada, balancing cost, speed and conversion), and Payment Risk (transfer suspensions, ACH and card chargebacks, and fraud). - Account: Owns how customers use Wise as an account, including getting paid into Wise with USD and CAD local account details, spending with the Wise debit card, and earning a return on money held with Wise. - Growth: Owns the top of the funnel, including landing pages, the promotion engine, corridor strategy, and pricing, working with our Pricing Data Science team. ## Your first six months - By three months: You own part of your team’s regular metrics and have delivered your first analysis. - By six months: You’ve led a discovery or an experiment readout from question to recommendation and presented it to your team. ## Qualifications - Education: A bachelor’s or master’s degree in a quantitative field such as economics, statistics, mathematics, computer science or engineering, completed by your start date, or equivalent practical experience. - Technical Foundations: You’ve used SQL, Python or R to answer a real question with data, in a course, a project, an internship or on your own. You understand the basics of statistics, such as distributions, hypothesis tests and confidence intervals. - Curiosity & Product Sense: You want to know why customers behave the way they do, and you ask “so what should we do?” about every result. - Clear Communication: You can explain a finding to someone who isn’t technical, in writing and in conversation, and you’re comfortable saying “I don’t know yet”. - Ownership: You finish what you start, ask for help early and act on feedback. - AI with Judgment: You use AI tools to work faster, and you check their output before you trust it. - Right to Work: You must be authorized to work in the US. Wise is unable to offer visa sponsorship for this role. ## Nice to have - Hands-on experience with any of Snowflake, dbt, Git, Airflow or Lightdash. - Exposure to A/B testing or causal inference, in a course or in practice. - An internship or project in analytics, data science, product or finance. - An interest in payments, fintech, or how people move and manage money across borders.